arXiv subjects

Man-Hong Yung

Publications and source records attributed to Man-Hong Yung.

At least 109 records · Page 6Linked to original sources

arXiv2019

Low-Depth Optical Neural Networks

Optical neural network (ONN) is emerging as an attractive proposal for machine-learning applications, enabling high-speed computation with low-energy consumption. However, there are several challenges in applying ONN for industrial applications, including the realization of activation functions and maintaining stability. In particular, the stability of ONNs decrease with the circuit depth, limiting the scalability of the ONNs for practical uses. Here we demonstrate how to compress the circuit depth of ONN to scale only logarithmically, leading to an exponential gain in terms of noise robustness. Our low-depth (LD) ONN is based on an architecture, called Optical CompuTing Of dot-Product UnitS (OCTOPUS), which can also be applied individually as a linear perceptron for solving classification problems. Using the standard data set of Letter Recognition, we present numerical evidence showing that LD-ONN can exhibit a significant gain in noise robustness, compared with a previous ONN proposal based on singular-value decomposition [Nature Photonics 11, 441 (2017)].

physics.optics↗

arXiv2019

Minimal Non-orthogonal Gate Decomposition for Qubits with Limited Control

In quantum control theory, a question of fundamental and practical interest is how an arbitrary unitary transformation can be decomposed into minimum number of elementary rotations for implementation, subject to various physical constraints. Examples include the singlet-triplet (ST) and exchange-only (EO) qubits in quantum-dot systems, and gate construction in the Solovay-Kitaev algorithm. For two important scenarios, we present complete solutions to the problems of optimal decomposition of single-qubit unitary gates with non-orthogonal rotations. For each unitary gate, we give the criteria for determining the minimal number of pieces, the explicit gate construction procedure, as well as a computer code for practical uses. Our results include an analytic explanation to the four-gate decomposition of EO qubits, previously determined numerically by Divincenzo et al [Nature, 408, 339 (2000)]. Furthermore, compared with the approaches of Ramon sequence and its variant [Phys. Rev. Lett., 118, 216802 (2017)], our method can reduce about 50% of gate time for ST qubits. Finally, our approach can be extended to solve the problem of optimal control of topological qubits, where gate construction is achieved through the braiding operations.

cond-mat.mes-hall↗

arXiv2019

Enhancement of antiferromagnetic magnon-magnon entanglement by cavity cooling

Magnon-photon coupling has been experimentally realized inside a cavity and the emerging field known as cavity spintronics has attracted significant attention for its potential docking with quantum information science. However, one seldom knows whether this coupling implies an entanglement state among magnons and photons or not, which is crucial for its usage in quantum information. Here we study the entanglement properties among magnons and photons in an antiferromagnet-light system and find that the entanglement between magnon and photon is nearly zero while the magnon-magnon entanglement is very strong and it can be even further enhanced through the coupling with the cavity photons. The maximum enhancement occurs when the antiferromagnet reaches resonant with the light. The essential physics can be well understood within the picture of cavity induced cooling of magnon-magnon state near its joint vacuum with stronger entanglement. Our results are significant to extend the cavity spintronics to quantum manipulation and further provide an alternate to manipulate the deep strong correlations of continuous variable entanglement with a generic stable condition and easy tunability.

cond-mat.mes-hall↗

arXiv2019

Black hole evaporation in Conformal (Weyl) gravity

In this work, we explore all possible scenarios in the evaporation process of a spherical neutral AdS black hole in four-dimensional conformal gravity, where the equations of states are branched. In one branch, the final states correspond to the extremal black hole where the total decay time is divergent given any initial mass. In the other branch, the black holes always evaporate completely with in a finite time; the total decay time depends linearly on the AdS radius, when the mass is taken to be infinity.

gr-qc↗

arXiv2019

Emergence of Network Bifurcation Triggered by Entanglement

In many non-linear systems, such as plasma oscillation, boson condensation, chemical reaction, and even predatory-prey oscillation, the coarse-grained dynamics are governed by an equation containing anti-symmetric transitions, known as the anti-symmetric Lotka-Volterra (ALV) equations. In this work, we prove the existence of a novel bifurcation mechanism for the ALV equations, where the equilibrium state can be drastically changed by flipping the stability of a pair of fixed points. As an application, we focus on the implications of the bifurcation mechanism for evolutionary networks; we found that the bifurcation point can be determined quantitatively by the microscopic quantum entanglement. The equilibrium state can be critically changed from one type of global demographic condensation to another state that supports global cooperation for homogeneous networks. In other words, our results indicate that there exist a class of many-body systems where the macroscopic properties are invariant with a certain amount of microscopic entanglement, but they can be changed abruptly once the entanglement exceeds a critical value. Furthermore, we provide numerical evidence showing that the emergence of bifurcation is robust against the change of the network topologies, and the critical values are in good agreement with our theoretical prediction. These results show that the bifurcation mechanism could be ubiquitous in many physical systems, in addition to evolutionary networks.

quant-ph↗

arXiv2019

Experimental Realization of Nonadiabatic Shortcut to Non-Abelian Geometric Gates

When a quantum system is driven adiabatically through a parametric cycle in a degenerate Hilbert space, the state would acquire a non-Abelian geometric phase, which is stable and forms the foundation for holonomic quantum computation (HQC). However, in the adiabatic limit, the environmental decoherence becomes a significant source of errors. Recently, various non-adiabatic HQC schemes have been proposed, but all at the price of increased sensitivity to control errors. Alternatively, there exist theoretical proposals for speeding up HQC by the technique of "shortcut to adiabaticity" (STA), but no experimental demonstration has been reported so far, as these proprosals involve a complicated control of four energy levels simultaneously. Here we propose and experimentally demonstrate that HQC via shortcut to adiabaticity can be constructed with only three energy levels, using a superconducting qubit in a scalable architecture. With this scheme, all holonomic single-qubit operations can be realized non-adiabatically through a single cycle of state evolution. As a result, we are able to experimentally benchmark the stability of STA+HQC against NHQC in the same platform. The flexibility and simplicity of our scheme makes it also implementable on other systems, such as nitrogen-vacancy center, quantum dots, and nuclear magnetic resonance.

quant-ph↗

arXiv2019

Optimal Mechanism for Randomized Responses under Universally Composable Security Measure

We consider a problem of analyzing a global property of private data through randomized responses subject to a certain rule, where private data are used for another cryptographic protocol, e.g., authentication. For this problem, the security of private data was evaluated by a universally composable security measure, which can be regarded as $(0,δ)$-differential privacy. Here we focus on the trade-off between the global accuracy and a universally composable security measure, and derive an optimal solution to the trade-off problem. More precisely, we adopt the Fisher information of a certain distribution family as the estimation accuracy of a global property and impose $(0,δ)$-differential privacy on a randomization mechanism protecting private data. Finally, we maximize the Fisher information under the $(0,δ)$-differential privacy constraint and obtain an optimal mechanism explicitly.

math.ST↗

arXiv2018

On the thermodynamic phase structure of conformal gravity

The solutions of the Einstein equation are a subset of the solutions of conformal (Weyl) gravity, but the difference from the action means that the black hole thermodynamics of the two gravity theories would be different. In this paper we explore the thermodynamic phase structure for the conformal gravity in the four-dimensional AdS space-time. Special emphasis is put on the dependence on the parameter $c_1$ in the linear-$r$ term in the metric. The thermodynamic phase structure of the conformal gravity is very rich, including two branches of equations of states, negative thermodynamic volume, zeroth-order phase transition, and Hawking-Page like phase transition.

gr-qc↗

arXiv2018

Quantum carpets from Gaussian sum theory

In many closed quantum systems, an interesting phenomenon, called quantum carpet, can be observed, where the evolution of wave function exhibits a carpet-like pattern. The mechanism of quantum carpet is similar to the classical interference pattern of light. Although the origin of quantum carpets has been studied previously, there are still many interesting details worth exploring. Here, we presented a unified framework for a simultaneous analyzing on three features of quantum carpets, namely full revival, fractional revival and diagonal canal. For fractional revival, a complete formula is presented to explain its generation through "Gaussian sum theory", in which all the essential features, including the phases and amplitudes, of this phenomenon could be captured analytically. Moreover, we also revealed the relations between the interference terms of the diagonal canals and their geometric interpretations, providing a better understanding in the formation of diagonal canals.

quant-ph↗

arXiv2018

Wiggling skyrmion propagation under parametric pumping

We address the problem of how magnetic skyrmions can propagate along a guided direction by parametric pumping. As evidenced by our micromagnetic simulations, skyrmions can hardly be driven by either a static electric field or a static magnetic field alone. Although the magnetic anisotropy can be modified by an electric field, parametric pumping with an oscillating electric field can only excite the breathing modes. On the other hand, a static magnetic field can break rotational symmetry through the Zeeman interaction, but it cannot serve as an energy source for propelling a skyrmion. Here we found that the combination of a perpendicularly oscillating electric field and an in-plane static magnetic field can drive a skyrmion undergoing a wiggling motion along a well defined trajectory. The most efficient driving occurs when the frequency of the oscillating field is close to that of the breathing motion. The physics is revealed in a generalized Thiele equation where a net spin current excited by the parametric pumping can drive the skyrmion propagation through angular momentum transfer. Compared with other alternative proposals, our results open new possibilities for manipulating skyrmions in both metals and insulators with low-power consumption. The oscillating skyrmion motion can also be a microwave generator for future spintronic applications such as an nano-tool on a diamond Nitrogen-Vacancy center.

cond-mat.mes-hall↗

arXiv2018

Experimental Machine Learning of Quantum States

Quantum information technologies provide promising applications in communication and computation, while machine learning has become a powerful technique for extracting meaningful structures in 'big data'. A crossover between quantum information and machine learning represents a new interdisciplinary area stimulating progresses in both fields. Traditionally, a quantum state is characterized by quantum state tomography, which is a resource-consuming process when scaled up. Here we experimentally demonstrate a machine-learning approach to construct a quantum-state classifier for identifying the separability of quantum states. We show that it is possible to experimentally train an artificial neural network to efficiently learn and classify quantum states, without the need of obtaining the full information of the states. We also show how adding a hidden layer of neurons to the neural network can significantly boost the performance of the state classifier. These results shed new light on how classification of quantum states can be achieved with limited resources, and represent a step towards machine-learning-based applications in quantum information processing.

quant-ph↗

arXiv2018

Quantifying Quantum Coherence in Experimentally-Observed Neutrino Oscillations

Neutrino oscillation represents an intriguing physical phenomenon where the quantumness can be maintained and detected over a long distance. Previously, the non-classical character of neutrino oscillation was tested with the Leggett-Garg inequality, where a clear violation of the classical bound was observed [J. A. Formaggio et al., Phys. Rev. Lett. 117, 050402 (2016)]. However, there are several limitations in testing neutrino oscillations with the Leggett-Garg inequality. In particular, the degree of violation of the Leggett-Garg inequality cannot be taken as a "measure of quantumness". Here we focus on quantifying the quantumness of experimentally-observed neutrino oscillation, using the tools of recently-developed quantum resource theory. We analyzed ensembles of reactor and accelerator neutrinos at distinct energies from a variety of neutrino sources, including Daya Bay (0.5 km and 1.6 km), Kamland (180 km), MINOS (735 km), and T2K (295 km). The quantumness of the three-flavoured neutrino oscillation is characterized within a 3σ range relative to the theoretical prediction. It is found that the maximal coherence was observed in the neutrino source from the Kamland reactor. However, even though the survival probability of the Daya Bay experiment did not vary significantly (dropped about 10 percent), the coherence recorded can reach up to 40 percent of the maximal value. These results represent the longest distance over which quantumness were experimentally determined for quantum particles other than photons.

hep-ph↗

arXiv2018

Automatic spin-chain learning to explore the quantum speed limit

One of the ambitious goals of artificial intelligence is to build a machine that outperforms human intelligence, even if limited knowledge and data are provided. Reinforcement Learning (RL) provides one such possibility to reach this goal. In this work, we consider a specific task from quantum physics, i.e. quantum state transfer in a one-dimensional spin chain. The mission for the machine is to find transfer schemes with fastest speeds while maintaining high transfer fidelities. The first scenario we consider is when the Hamiltonian is time-independent. We update the coupling strength by minimizing a loss function dependent on both the fidelity and the speed. Compared with a scheme proven to be at the quantum speed limit for the perfect state transfer, the scheme provided by RL is faster while maintaining the infidelity below $5\times 10^{-4}$. In the second scenario where a time-dependent external field is introduced, we convert the state transfer process into a Markov decision process that can be understood by the machine. We solve it with the deep Q-learning algorithm. After training, the machine successfully finds transfer schemes with high fidelities and speeds, which are faster than previously known ones. These results show that Reinforcement Learning can be a powerful tool for quantum control problems.

cond-mat.mes-hall↗

arXiv2018

Neural-network-designed pulse sequences for robust control of singlet-triplet qubits

Composite pulses are essential for universal manipulation of singlet-triplet spin qubits. In the absence of noise, they are required to perform arbitrary single-qubit operations due to the special control constraint of a singlet-triplet qubits; while in a noisy environment, more complicated sequences have been developed to dynamically correct the error. Tailoring these sequences typically requires numerically solving a set of nonlinear equations. Here we demonstrate that these pulse sequences can be generated by a well-trained, double-layer neural network. For sequences designed for the noise-free case, the trained neural network is capable of producing almost exactly the same pulses known in the literature. For more complicated noise-correcting sequences, the neural network produces pulses with slightly different line-shapes, but the robustness against noises remains comparable. These results indicate that the neural network can be a judicious and powerful alternative to existing techniques, in developing pulse sequences for universal fault-tolerant quantum computation.

quant-ph↗

arXiv2018

Strong entanglement of spins inside a quantum domain wall

Magnetic domain walls (DWs) are widely regarded as classical objects in physics community, even though the concepts of electron spins and spin-spin exchange interaction are quantum mechanical in nature. One intriguing question is whether DWs can survive at the quantum level and acquire the quantum properties such as entanglement. Here we show that spins within a DW are highly entangled in their quantum description. The total magnetization of a magnetic DW is nonzero, which is a manifestation of the global entanglement of the collective spin state. These results significantly deepen our understanding of magnetic DWs and enable the application of DWs in quantum information science. The essential physics can be generalized to skyrmions so that they can also play a role in quantum information processing.

cond-mat.mes-hall↗

arXiv2018

One-Shot Detection Limits of Quantum Illumination with Discrete Signals

A minimally-invasive way to detect the presence of a stealth target is to probe it with a single photon and analyze the reflected signals. The efficiency of such a conventional detection scheme can potentially be enhanced by the method of quantum illumination, where entanglement is exploited to break the classical limits. The question is, what is the optimal quantum state that allows us to achieve the detection limit with a minimal error? Here we address this question for discrete signals, by deriving a complete and general set of analytic solutions for the whole parameter space, which can be classified into three distinct regions, in the form of phase diagrams for both conventional and quantum illumination. Interestingly, whenever the reflectivity of the target is less than some critical values, all received signals become useless, which is true even if entangled resources are employed. However, there does exist a region where quantum illumination can provide advantages over conventional illumination; there, the optimal signal state is an entangled state with an entanglement spectrum inversely proportional to the spectrum of the environmental state. These results not only impose fundamental limits in applications such as quantum radars, but also suggest how to become immune against the attack of minimally-invasive detection.

quant-ph↗

arXiv2018

Spontaneous Valley Splitting and Valley Pseudospin Field Effect Transistor of Monolayer VAgP2Se6

Valleytronics is a rising topic to explore the emergent degree of freedom for charge carriers in energy band edges and has attracted a great interest due to many intriguing quantum phenomena and potential application in information processing industry. Creation of permanent valley polarization, i.e. unbalanced occupation at different valleys, is a chief challenge and also urgent question to be solved in valleytronics. Here we predict that the spin-orbit coupling and magnetic ordering allow spontaneous valley Zeeman-type splitting in pristine monolayer of VAgP2Se6 by using first-principles calculations. The Zeeman-type valley splitting can lead to permanent valley polarization after suitable doping. The Zeeman-type valley splitting is similar to the role of spin polarization in spintronics and is a vital requirement for practical devices in valleytronics. The nonequivalent valleys of VAgP2Se6 monolayer can emit or absorb circularly polarized photons with opposite chirality, and thus this material shows a great potential to work as a photonic spin filter and circularly-polarized-light resource. A valley pseudospin field effect transistor (VPFET) is designed based on the monolayer VAgP2Se6 akin to the spin field effect transistors. Beyond common transistors, VPFETs carry information of not only the electrons but also the valley pseudospins.

cond-mat.mtrl-sci↗

arXiv2017

Holevo Bound of Entropic Uncertainty in Schwarzschild Spacetime

For a pair of incompatible quantum measurements, the total uncertainty can be bounded by a state-independent constant. However, such a bound can be violated if the quantum system is entangled with another quantum system (called memory); the quantum correlation between the systems can reduce the measurement uncertainty. On the other hand, in a curved spacetime, the presence of the Hawking radiation can increase the uncertainty in quantum measurement. The interplay of quantum correlation in the curved spacetime has become an interesting arena for studying quantum uncertainty relations. Here we demonstrate that the bounds of the entropic uncertainty relations, in the presence of memory, can be formulated in terms of the Holevo quantity, which limits how much information can be encoded in a quantum system. Specifically, we considered two examples with Dirac fields, near the event horizon of a Schwarzschild black hole, the Holevo bound provides a better bound than the previous bound based on the mutual information. Furthermore, if the memory moves away from the black hole, the difference between the total uncertainty and the Holevo bound remains a constant, not depending on any property of the black hole.

quant-ph↗